PwC data accelerator

Building an AI-assisted data migration platform at speed with Kiro

Build as a service

Rapid six-week delivery

A lean team delivered the PwC Data Accelerator from discovery to a production-ready MVP in just six weeks, using Kiro and AI agents to accelerate development.

AI-powered migration automation

The platform demonstrated an end-to-end migration approach, from extracting source and target data structures and proposing validated mappings to generating assets and executing workflows.

Reusable migration assets

Automated validation reports, documentation and reusable artefacts provided a standardised approach to migration, supporting consistency and long-term success.

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SITUATION

Overview

Data migration is a critical service offering for PwC, yet every client engagement has traditionally followed a different approach. Migration teams would create new mapping spreadsheets, bespoke scripts, and project documentation for each engagement, resulting in significant manual effort, inconsistent quality, and limited reuse between projects.

The business needed to create a standardised, repeatable approach to data migrations that could reduce repetitive effort, accelerate delivery, and improve consistency, while ensuring engineers remained in control of migration decisions.

PwC commissioned the development of the Data Accelerator, an AI-assisted platform designed to guide engineers through a single "golden path" for migrations, from source system discovery through to migration validation.

The project was ambitious with a compressed timeline of just six weeks, and a small delivery team. To succeed, the team adopted an AI-native delivery approach centred around Kiro.

Solution

The approach

Leighton partnered with PwC to design and build the Data Accelerator, an internal AI-assisted CLI platform that standardises the migration lifecycle while keeping engineers firmly in the review and approval loop.

The solution provides a repeatable workflow that guides migration teams through five core stages:

Extract source and target structures

Map fields using AI-assisted recommendations

Generate migration artefacts and scripts

Execute migration runs

Validate results against expected outcomes

Using Amazon Bedrock, the platform proposes field-level mappings complete with confidence scores, conversion recommendations, and validation against the target schema. Engineers review and approve proposals before progressing, ensuring a human-in-the-loop approach throughout.

All outputs are produced as standardised artefacts and stored in a version-controlled workspace, making migration activities reusable, auditable, and repeatable across engagements.

The architecture was designed around extensibility from day one, with a ports-and-adapters approach enabling support for additional database technologies and migration patterns without requiring significant changes to the core platform.

Delivering with Kiro

A key objective was not simply to build a data migration accelerator, but to demonstrate how agentic development practices could transform software delivery.

Kiro became the primary development and orchestration platform throughout the project, supporting the full lifecycle from research, technical discovery and architectural decisions through to product requirements, scope definition, technical design and delivery planning.

As the project moved into construction, Kiro continued to support implementation, testing, refactoring, validation and quality assurance. This maintained continuity between discovery and delivery, significantly reducing context switching and documentation drift.

Establishing a shared delivery intelligence

To maximise consistency, the team implemented Kiro Steering Documents that embedded the product vision, technical architecture, ways of working, coding standards, repository structure, product requirements and delivery objectives directly into the development workflow.

These documents gave every agent a shared understanding of the project, reducing the need to repeatedly explain context and ensuring outputs aligned with team expectations.

The result was a development environment where AI agents could operate with the same understanding of the project as the engineering team.

Tech Stack

The solution combined Kiro’s agentic development environment, Steering Documents, Hooks, Custom Agents and MCP integrations with AWS services, including Amazon Bedrock and a cloud-native architecture. Delivery followed an AI-Driven Software Development Lifecycle (AIDLC), incorporating mob elaboration, mob construction, ADR-driven architecture and human-in-the-loop AI governance to accelerate development while maintaining quality, consistency and control.

AWS Kiro

Amazon Bedrock

IMPACT

Delivering AI-powered enterprise transformation
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The PwC Data Accelerator established a repeatable, AI-assisted approach to client data migrations whilst proving the effectiveness of agentic delivery at enterprise scale.

Through the combination of Kiro, Amazon Bedrock, and a highly collaborative engineering model, PwC gained both a migration accelerator and a blueprint for how future software products can be rapidly delivered using AI-assisted engineering practices.

Rapid six-week delivery
A lean team delivered the PwC Data Accelerator from discovery to a production-ready MVP in just six weeks, using Kiro and AI agents to accelerate development.
AI-powered migration automation
The platform demonstrated an end-to-end migration approach, from extracting source and target data structures and proposing validated mappings to generating assets and executing workflows.
Reusable migration assets
Automated validation reports, documentation and reusable artefacts provided a standardised approach to migration, supporting consistency and long-term success.
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Accelerated agentic delivery
Embedding Kiro throughout the delivery lifecycle demonstrated how AI agents, combined with strong engineering practices and human oversight, can significantly accelerate project execution while maintaining quality and governance.
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Lean team, amplified delivery
A small team of an architect-developer and two senior engineers leveraged AI agents to increase delivery capacity and coordinate development efficiently.
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Built-in quality and governance
The engagement embedded quality controls, governance and human oversight throughout delivery, ensuring the MVP was supported by the documentation and knowledge assets needed for long-term success.
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Build as a service

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Building an AI-assisted data migration platform at speed with Kiro

Overview

The approach

Delivering with Kiro

Establishing a shared delivery intelligence

Tech Stack

Delivering AI-powered enterprise transformation‍

Let's talk about your next project.

Thank you!

Delivering AI-powered enterprise transformation
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